Overview

Dataset statistics

Number of variables4
Number of observations100000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.5 MiB
Average record size in memory193.8 B

Variable types

Numeric3
Categorical1

Reproduction

Analysis started2024-02-18 15:32:46.607570
Analysis finished2024-02-18 15:44:13.580982
Duration11 minutes and 26.97 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

user_id
Real number (ℝ)

Distinct943
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean462.48475
Minimum1
Maximum943
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2024-02-18T15:44:13.754583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile46
Q1254
median447
Q3682
95-th percentile892
Maximum943
Range942
Interquartile range (IQR)428

Descriptive statistics

Standard deviation266.61442
Coefficient of variation (CV)0.57648262
Kurtosis-1.0973667
Mean462.48475
Median Absolute Deviation (MAD)213
Skewness0.082533291
Sum46248475
Variance71083.249
MonotonicityNot monotonic
2024-02-18T15:44:14.060246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
405 737
 
0.7%
655 685
 
0.7%
13 636
 
0.6%
450 540
 
0.5%
276 518
 
0.5%
416 493
 
0.5%
537 490
 
0.5%
303 484
 
0.5%
234 480
 
0.5%
393 448
 
0.4%
Other values (933) 94489
94.5%
ValueCountFrequency (%)
1 272
0.3%
2 62
 
0.1%
3 54
 
0.1%
4 24
 
< 0.1%
5 175
0.2%
6 211
0.2%
7 403
0.4%
8 59
 
0.1%
9 22
 
< 0.1%
10 184
0.2%
ValueCountFrequency (%)
943 168
0.2%
942 79
0.1%
941 22
 
< 0.1%
940 107
0.1%
939 49
 
< 0.1%
938 108
0.1%
937 40
 
< 0.1%
936 142
0.1%
935 39
 
< 0.1%
934 174
0.2%

item_id
Real number (ℝ)

Distinct1682
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean425.53013
Minimum1
Maximum1682
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2024-02-18T15:44:14.353462image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile30
Q1175
median322
Q3631
95-th percentile1074
Maximum1682
Range1681
Interquartile range (IQR)456

Descriptive statistics

Standard deviation330.79836
Coefficient of variation (CV)0.7773794
Kurtosis0.42253411
Mean425.53013
Median Absolute Deviation (MAD)196
Skewness0.9863565
Sum42553013
Variance109427.55
MonotonicityNot monotonic
2024-02-18T15:44:14.651563image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 583
 
0.6%
258 509
 
0.5%
100 508
 
0.5%
181 507
 
0.5%
294 485
 
0.5%
286 481
 
0.5%
288 478
 
0.5%
1 452
 
0.5%
300 431
 
0.4%
121 429
 
0.4%
Other values (1672) 95137
95.1%
ValueCountFrequency (%)
1 452
0.5%
2 131
 
0.1%
3 90
 
0.1%
4 209
0.2%
5 86
 
0.1%
6 26
 
< 0.1%
7 392
0.4%
8 219
0.2%
9 299
0.3%
10 89
 
0.1%
ValueCountFrequency (%)
1682 1
< 0.1%
1681 1
< 0.1%
1680 1
< 0.1%
1679 1
< 0.1%
1678 1
< 0.1%
1677 1
< 0.1%
1676 1
< 0.1%
1675 1
< 0.1%
1674 1
< 0.1%
1673 1
< 0.1%

rating
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.7 MiB
4.0
34174 
3.0
27145 
5.0
21201 
2.0
11370 
1.0
6110 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters300000
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row3.0
3rd row1.0
4th row2.0
5th row1.0

Common Values

ValueCountFrequency (%)
4.0 34174
34.2%
3.0 27145
27.1%
5.0 21201
21.2%
2.0 11370
 
11.4%
1.0 6110
 
6.1%

Length

2024-02-18T15:44:14.981403image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-02-18T15:44:15.278482image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
4.0 34174
34.2%
3.0 27145
27.1%
5.0 21201
21.2%
2.0 11370
 
11.4%
1.0 6110
 
6.1%

Most occurring characters

ValueCountFrequency (%)
. 100000
33.3%
0 100000
33.3%
4 34174
 
11.4%
3 27145
 
9.0%
5 21201
 
7.1%
2 11370
 
3.8%
1 6110
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200000
66.7%
Other Punctuation 100000
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 100000
50.0%
4 34174
 
17.1%
3 27145
 
13.6%
5 21201
 
10.6%
2 11370
 
5.7%
1 6110
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 100000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 300000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 100000
33.3%
0 100000
33.3%
4 34174
 
11.4%
3 27145
 
9.0%
5 21201
 
7.1%
2 11370
 
3.8%
1 6110
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 100000
33.3%
0 100000
33.3%
4 34174
 
11.4%
3 27145
 
9.0%
5 21201
 
7.1%
2 11370
 
3.8%
1 6110
 
2.0%

time
Real number (ℝ)

Distinct49282
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.8352885 × 108
Minimum8.7472471 × 108
Maximum8.9328664 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2024-02-18T15:44:15.558058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum8.7472471 × 108
5-th percentile8.7532031 × 108
Q18.7944871 × 108
median8.8282694 × 108
Q38.8825998 × 108
95-th percentile8.9171789 × 108
Maximum8.9328664 × 108
Range18561928
Interquartile range (IQR)8811274.5

Descriptive statistics

Standard deviation5343856.2
Coefficient of variation (CV)0.0060483098
Kurtosis-1.1687487
Mean8.8352885 × 108
Median Absolute Deviation (MAD)3886481
Skewness0.1738863
Sum8.8352885 × 1013
Variance2.8556799 × 1013
MonotonicityNot monotonic
2024-02-18T15:44:15.861572image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
891033606 12
 
< 0.1%
879440109 10
 
< 0.1%
880822060 10
 
< 0.1%
879874388 10
 
< 0.1%
885546577 10
 
< 0.1%
891293606 10
 
< 0.1%
875428765 10
 
< 0.1%
891500028 10
 
< 0.1%
879966498 10
 
< 0.1%
888637768 10
 
< 0.1%
Other values (49272) 99898
99.9%
ValueCountFrequency (%)
874724710 1
< 0.1%
874724727 1
< 0.1%
874724754 1
< 0.1%
874724781 1
< 0.1%
874724843 1
< 0.1%
874724882 2
< 0.1%
874724905 1
< 0.1%
874724937 1
< 0.1%
874724988 1
< 0.1%
874725081 1
< 0.1%
ValueCountFrequency (%)
893286638 7
< 0.1%
893286637 3
< 0.1%
893286603 1
 
< 0.1%
893286584 1
 
< 0.1%
893286550 3
< 0.1%
893286511 2
 
< 0.1%
893286502 1
 
< 0.1%
893286501 3
< 0.1%
893286491 1
 
< 0.1%
893286373 1
 
< 0.1%

Interactions

2024-02-18T15:37:49.328132image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-18T15:32:58.130419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-18T15:35:21.420237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-18T15:39:25.291619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-18T15:33:10.285601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-18T15:35:34.223628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-18T15:40:59.929174image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-18T15:33:26.043352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-02-18T15:35:54.357689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-02-18T15:44:16.108595image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
item_idratingtimeuser_id
item_id1.0000.2600.027-0.007
rating0.2601.000-0.0120.001
time0.027-0.0121.0000.044
user_id-0.0070.0010.0441.000

Missing values

2024-02-18T15:44:12.992681image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-18T15:44:13.334291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

user_iditem_idratingtime
01962423.0881250949
11863023.0891717742
2223771.0878887116
3244512.0880606923
41663461.0886397596
52984744.0884182806
61152652.0881171488
72534655.0891628467
83054513.0886324817
96863.0883603013
user_iditem_idratingtime
999908064214.0882388897
999916765384.0892685437
999927212623.0877137285
999939132092.0881367150
99994378783.0880056976
999958804763.0880175444
999967162045.0879795543
9999727610901.0874795795
99998132252.0882399156
99999122033.0879959583